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Green Buildings Are Better – Financial Performance


A study by the Department of Energy found that in green buildings net operating income was 28.8% higher than in non-green buildings. Missouri has more green buildings than Tennessee, but far fewer than Maryland.


The residential and commercial buildings in the U.S. consume about 40% of the nation’s total energy consumption. Green buildings use less energy, improve occupant health and productivity, and lower ownership risk. However, until recently researchers have lacked sufficient historical data to analyze the link between energy efficiency and financial performance because the information has been proprietary.

A recent study by the U.S. Department of Energy addressed this question. The authors were able to identify a set of 131 buildings for which the necessary data were available. Only buildings that met the following criteria were accepted into the study:

  • Market value per square foot was greater than $400.
  • Rent concessions in the building were greater than $0, but less than $3 per square foot.
  • Monthly rent in the building was greater than $6 per square foot.
  • Occupancy in the building was greater than 50%.

The authors then divided the buildings into two groups: buildings were “green” if they had an Energy Star score of 75 or higher (a measure of energy efficiency compared to other buildings of the same type) or if they had achieved LEED Certification. A discussion of what these criteria mean is below. Buildings were “non-green” if they did not meet either criteria. The result was 2 groups of buildings, green and non-green, each with more than 60 buildings in it.

The authors then compared the buildings on the following metrics:

  • Market value per square foot;
  • Net operating Income per square foot;
  • Operating expenses per square foot;
  • Rental income per square foot;
  • Rental concessions per square foot;
  • Occupancy rate.

Table 1. Comparison of Green and Non-Green Buildings on 6 Financial Performance Metrics. Source: Department of Energy, 2017.

Table 1 gives the results. Green buildings had higher market value, higher net operating income, higher rent, lower rental concessions, lower operating expenses, and higher occupancy rates. The differences in operating expenses and net operating income achieved statistical significance (p = 0.0089 and 0.0015 respectively), and the difference in market value approached it (p = 0.094).

Looking at Table 1, what jumps out is that net operating income was 28.8% higher in green buildings. Most of the increase seems to have come from reduced expenses, with a smaller contribution coming from increased rents.

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Table 2. Source: Miller et al, 2008.

The Department of Energy study is not the only study to suggest better financial performance from green buildings. Table 2 summarizes results from 3 additional studies, all of which found that LEED and ENERGY STAR buildings generated higher rents, higher occupancy rates, and higher value per square foot.

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Figure 1. Data source: Green Building Information Gateway

So how many green buildings are there in Missouri? A database operated by the U.S. Green Building Council lists 389 LEED certifications in Missouri, covering 35.27 million square feet. Tennessee, Missouri, and Maryland are the 17th, 18th, and 19th most populous states in the country. Tennessee has 377 LEED certified activities (48.35 million square feet), and Maryland has 964 (11.4 million square feet). Figure 1 shows the data, with the number of LEED certified buildings in blue and the LEED certified square footage in red. Clearly, green building has caught on in Maryland to a much greater extent than it has here. It’s too bad – if you could deliver health benefits to those who live and work in a building, while at the same time improving its net operating income by 28.8%, you’d think that you’d want to do that, wouldn’t you?

Explanation of Energy Star and LEED Certification: ENERGY STAR is a building energy benchmarking program operated by the U.S. Department of Energy. Building owners enter their building’s energy consumption (from utility bills and similar sources) into a computer database. The database then compares the building’s energy consumption to that of other similar buildings. In other words, hospitals are compared to hospitals, schools to schools, office buildings to office buildings, etc. The program then gives each building a rating from 1-100, the higher the number the better the building’s energy performance. LEED is an acronym that stands for Leadership in Energy and Environmental Design. To achieve LEED certification, a building must incorporate a suite of technologies that improve the building’s environmental performance in a number of areas, from energy consumption to indoor air quality to water consumption, and others. The LEED system is administered by the U.S. Green Building Council.

MoGreenStats is now going on break for a few weeks. The next post will be scheduled for August 24, 2017. Happy trails ’til then.

Sources:

Department of Energy. 2017. Utilizing Commercial Real Estate Owner and Investor Data to Analyze the Financial Performance of Energy Efficient, High Performance Office Buildings. Downloaded 7/9/2017 from https://energy.gov/sites/prod/files/2017/05/f34/bto_PilotResearchStudy-DOEFinancialDataInitiative_5-8-17.pdf.

Miller, Norm, Jay Spivey, and Andy Florance. 2008. Does Green Pay Off? Published by U.S. Department of Energy. Downloaded 7/10/2017 from https://www.energystar.gov/sites/default/files/buildings/tools/DoesGreenPayOff.pdf.

The Green Building Information Gateway, an online database operated by the U.S. Green Building Council. Data accessed online 7/9/2017 at http://www.gbig.org.

Green Buildings are Better – Health


Green buildings have better indoor environmental qualities, and deliver direct health benefits to those who work in them or live in them.


Americans spend an average of 90% of their time indoors. Indoor environments with low air circulation can concentrate pollutants 2 to 5 times higher than in outdoor air. Contaminants found in indoor air include organic compounds (e.g. formaldehyde, pesticide, fire retardant), microbes (e.g. bacteria, mold), inorganic gases (e.g. ozone, carbon monoxide, radon), and particulate matter (second-hand smoke, dust, smoke from fires).

Building-related illnesses include infections (e.g. Legionnaire’s disease), headache, nausea, nasal and chest congestion, wheezing, eye problems, sore throat, fatigue, chills and fever, muscle pain, neurological symptoms, and dry skin. That’s quite a list, and it should be apparent that indoor environmental quality is very important to health and well-being.

Green buildings have better indoor environmental qualities, and deliver direct health benefits to those who work in them or live in them, according to a review conducted in 2015. The review looked at 17 different studies of the relationship between green buildings and health. Green buildings had lower levels of volatile organic compounds, formaldehyde, allergens, nitrous oxide, smoke, and particulate matter.

The improved indoor environmental quality translated to improved self-reported health outcomes, and improved self-reported productivity. Only one study used objective health outcome metrics, but it is instructive. Thiel et al compared results at a children’s hospital in Pittsburgh before and after it moved from a non-green to a green facility. After the move, there was less employee turnover and open positions filled faster. Blood stream infection rates declined 70% and the number of corrections that had to be made to medical records declined 49%. Not only that, but patient mortality was expected to be 11% higher after the move, because the case load became more severe. However, the green hospital actually had a 19% decrease in patient mortality.

In a more traditional office setting, 263 employees were studied before and after they moved from a non-green building to a green one. After moving, they reported a 56% decrease in absences due to asthma and respiratory allergies, a 49% decrease in absences due to depression and stress, and an improvement in productivity (productivity was measured using an index that does not lend itself to a numerical comparison of before and after).

Thus, the data look promising for green buildings. At the same time, confounding factors could explain some of the improvements observed, and the fact that many studies used self-report data suggests that caution should be used in interpreting the studies. Studies using more objective data are needed.

What about the financial performance of green buildings? The next post will explore that.

Sources:

Allen, Joseph, Piers MacNaughton, Jose Laurent, Skye Flanigan, Erika Eitland, and John Spengler. 2015. “Green Buildings and Health.” Current Environmental Health Report. Downloaded 7/9/2017 from https://link.springer.com/content/pdf/10.1007%2Fs40572-015-0063-y.pdf.

Singh, Amanjeet, Matt Syal, Sue Grady, and Sinem Korkmaz. 2010. “Effects of Green Buildings on Employee Health and Productivity.”

Thiel, C.L., Needy, K.L., Ries, R.J., Hupp, D., Bilec, M.M. (2014). “Building Design and Performance: A Comparative Longitudinal Assessment of a Children’s Hospital.” Building and the Environment. 78, August 2014, 130–136.
American Journal of Public Health. 1665-1668. Downloaded 7/9/2017 from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2920980.

U.S. Institute of Medicine. 2007. Green Healthcare Institutions: Health, Environment, and Economics: Workshop Summary, Chapter 4. The Health Aspects of Green Buildings. National Academies Press. Viewed online 6/10/2017 at https://www.ncbi.nlm.nih.gov/books/NBK54149.

Why 543 ppm CO2e Matters

In the last post I reviewed a report from the World Meteorological Organization; it said that in 2015 the atmospheric concentration of carbon dioxide reached 400 ppm for the first time. The methane and nitric oxide concentrations were 1,845 ppb and 328 ppb. Combined, I calculated that the 3 gases had a radiative forcing equal to 543 ppm CO2e.

[Note: When first published, this post contained a typographical error: in the title and in the first paragraph, I reported the CO2e as ppb (parts per billion). Parts per million (ppm) is correct, and I have made the change.]

More recent data from the Mauna Loa Observatory indicates that, since 2015, the atmospheric concentration of carbon dioxide has climbed to 409.65, meaning that the combined radiative forcing is now even higher. But what do these numbers mean? I will try to explain.

Most scientists studying climate change have emphasized that it is already too late to avoid its effects entirely – they are already happening. My recent posts on the declining snowpack of the western United States are just one example. I’ve also published numerous posts documenting the increase in temperature in Missouri and other states, the USA as a whole, and the world as a whole.

Figure 1. Source: IPCC 2014.

Scientists have also emphasized that the effects of climate change will depend on how much the temperature increases. The more the temperature increases, the more severe the effects will be. Figure 1 illustrates the conceptualization. In the chart, each column represents a system that climate change will affect. The 2 y-axis scales represent temperature change, the scale on the left relative to the period from 1986-2000, the one on the right relative to 1850-1900. The color coding of the columns represents the degree of risk that is projected. White and yellow represent less risk, red and purple represent more. There are no cut-off points in this graph, but you can see that as the temperature increases more than 2°C (relative to 1986-2000), the risk grows from moderate to high or very high.

How much the temperature will actually increase depends on how high radiative forcing goes, which will depend on the atmospheric concentration of GHGs. Carbon dioxide is the principal GHG.

Figure 2. Data source: Earth Systems Research Laboratory 2017b.

Figure 2 shows the average annual carbon dioxide concentration measured at the Mauna Loa Observatory from 1959 through 2016 in blue. During the last 10 years, the concentration grew an average of 0.57% each year. In red, Figure 1 projects the carbon dioxide concentration through 2100, assuming that it continues to grow at that rate each year. By 2100, the carbon dioxide concentration will have reached 651 ppm.

The future atmospheric concentration of GHGs depends on how much we continue to emit. To study the possibilities, scientists use a series of scenarios that range from sharply reduced emissions, through a middle ground, to very high emissions. They have changed the names they give these scenarios, and now call them RCP2.6, RCP4.5, RCP6, and RCP8.5. RCP6 is associated with a carbon dioxide concentration in 2100 that is similar to the 651 ppm projection I calculated above. Thus, if emissions continue to grow at the same rate, the earth will approximate the RCP6 scenario.

Now, as I noted in the last post, the growth in the atmospheric concentration of carbon dioxide seems to be accelerating. Thus, there is some question regarding whether the earth really is following the RCP6 scenario or something worse. For now, I will stay with RCP6.

Figure 3. Projected Temperature Increase Under Four RCP Scenarios. Source: Collins et al, 2013.

Figure 3 shows the mean temperature increase that is projected to occur under each RCP scenario, with RCP6 in orange. By 2100, a temperature increase of about 2°C is projected to occur. (One additional thing to note about this chart: the temperature increase under RCP6 and RCP 8.5 does not stabilize by 2100 – the temperature will continue to increase thereafter.)

Okay, now we’ve got what we need to draw some simple conclusions. The atmospheric concentration of carbon dioxide is increasing at a rate that, if it continues, will approximate the RCP6 scenario. That scenario is associated with a temperature increase of about 2°C compared to 1986-2000, and an even higher temperature thereafter. At that temperature increase, unique and sensitive systems will already be experiencing severe risk. And at that temperature increase, the global aggregate risk will grow from medium to high.

Well, if you come away thinking it is all a bit complex and vague, if not downright mealy-mouthed, I wouldn’t blame you. Climate scientists used to speak more directly, but then they came under attack from those who wanted to destroy them, and those days are gone. If you want to think further about the implications of all this, then think about these questions:

  1. What does it mean for the health of the planet, and for the health of our species on this planet, that we are following a course that puts unique and vulnerable systems under high risk? It’s already happening, just look around.
  2. What does it mean that we are following a course that will cause moderate-to-high aggregate global risk? What will the impacts be, and how will human life be affected?
  3. What does it mean for the health of the planet, and for the health of our species on this planet, that the increase in the concentration of carbon dioxide is not decelerating, but continuing to accelerate? The Kyoto Protocol was signed 20 years ago, and it was 11 years ago that climate change burst into widespread consciousness with Al Gore’s An Inconvenient Truth. What does it mean that we have known for so long that we need to address this problem, yet atmospheric GHG concentration growth continues to accelerate?
  4. What does it mean that, in the face of these facts, we elected a President who is hostile to the idea of climate change, and he appointed an EPA Administrator who is, also.
  5. Even absent our current President and EPA Administrator, have we shown any sign of being willing or able to undertake and accomplish the large-scale changes that will be necessary to address these problems?

The reality we face is becoming more dire each day, dear readers. We are passing danger signs like they mean nothing. We will have to live with the consequences for a very long time.

Sources:

Collins, M., R. Knutti, J. Arblaster, J.-L. Dufresne, T. Fichefet, P. Friedlingstein, X. Gao, W.J. Gutowski, T. Johns, G. Krinner, M. Shongwe, C. Tebaldi, A.J. Weaver and M. Wehner, 2013: Long-term Climate Change: Projections, Com- mitments and Irreversibility. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Earth System Research Laboratory. 2017 b. Mauna Loa CO2 Annual Mean Data. Downloaded 2017-06-15 from https://www.esrl.noaa.gov/gmd/ccgg/trends.

IPCC, 2013: Summary for Policymakers. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

IPCC 2014: Summary for policymakers. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Field, C.B., V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1-32.

World Meteorological Organization. 2016. WMO Greenhouse Gas Bulletin: The State of Greenhouse Gases in the Atmosphere Based on Global Observations through 2015. Number 12, 24 October 2016. Downloaded 6/15/2017 from http://www.wmo.int/pages/prog/arep/gaw/ghg/GHGbulletin.html.

World Carbon Dioxide Concentration Above 400 ppm. for the First Time Ever


In 2015 the concentration of carbon dioxide was 400 ppm, for the first time ever. The atmospheric concentration of carbon dioxide equivalent (CO2e) was 543 ppm.


Figure 1. Atmospheric Concentrations of GHGs in 2015 and Radiative Forcing from 1979-2015. Source: World Meteorological Organization.

In this post I will catch up with the Greenhouse Gas Bulletin published by the World Meteorological Society in October, 2016. It concerns atmospheric GHGs during 2015.

For the first time ever, the global concentration of carbon dioxide averaged 400 ppm, while the concentration of methane rose to 1,845 ppb, and the concentration of nitrous oxide rose to 328.0 ppb. These represent growth from 2014 of 0.58%, 0.60%, and 0.31%, respectively. The concentration of carbon dioxide is now 144% of what it was in 1750, while methane is 256% and nitrous oxide is 121%. The data are shown in Figure 1.

The report does not calculate the carbon dioxide equivalent of the three combined, but simply multiplying methane and nitrous oxide by their global warming potentials yields a combined carbon dioxide equivalent of 543 (using the 100-year global warming potentials published in the IPCC 4th AR).

Radiative forcing (the warming effect) of these GHGs was approximately 3.0 watts per meter in 2015 above 1750, compared to approximately 1.7 in1979.

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Figure 2. Source: Earth Systems Research Laboratory, 2017c.

Figure 2 shows the recent data on carbon dioxide concentration as measured at the Mauna Loa Observatory. The red line represents the actual measured value, and the black line represents the trend. This location is often taken as the best place to measure atmospheric carbon dioxide concentrations because it is in the middle of the Pacific Ocean, far away from large local sources of carbon dioxide, high in the atmosphere, and buffeted by almost constant trade winds. The chart shows that the concentration of carbon dioxide surges each winter, then ebbs each summer. This seasonal effect is due to the summer greening of the Northern Hemisphere, where the bulk of the world’s land mass is. Once it has greened, the vegetation absorbs carbon dioxide and converts it to oxygen as part of the process of photosynthesis, pulling it out of the atmosphere. After the vegetation goes dormant during the winter, it does not absorb carbon dioxide, and the concentration increases.

The reading for May, 2017 was 409.65 ppm.

Earth Systems Research Laboratory, 2017 a.

Figure 3 shows the same data going back to the late 1950s. Though the concentration of carbon dioxide surges and ebbs each year, you can see that the trend is irrevocably upward. The peak each winter is higher than the previous winter’s high, and the low point each summer is higher than the previous summer’s low. At no time has this trend ever reversed, in fact it has never even slowed. If anything, the trend is curving upward, meaning it is increasing faster.

In the next post I will discuss what these findings mean.

Sources:

Forster, P., V. Ramaswamy, P. Artaxo, T. Berntsen, R. Betts, D.W. Fahey, J. Haywood, J. Lean, D.C. Lowe, G. Myhre, J. Nganga, R. Prinn, G. Raga, M. Schulz and R. Van Dorland, 2007: Changes in Atmospheric Constituents and in Radiative Forcing. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Earth System Research Laboratory. 2017a. Full Mauna Loa CO2 Record. Downloaded 2017-06-15 from https://www.esrl.noaa.gov/gmd/ccgg/trends.

Earth System Research Laboratory. 2017b. Mauna Loa CO2 Annual Mean Data. Downloaded 2017-06-15 from https://www.esrl.noaa.gov/gmd/ccgg/trends.

Earth System Research Laboratory. 2017c. Recent Monthly Average Mauna Loa CO2. Downloaded 2017-06-15 from https://www.esrl.noaa.gov/gmd/ccgg/trends.

World Meteorological Organization. 2016. WMO Greenhouse Gas Bulletin: The State of Greenhouse Gases in the Atmosphere Based on Global Observations through 2015. Number 12, 24 October 2016. Downloaded 6/15/2017 from http://www.wmo.int/pages/prog/arep/gaw/ghg/GHGbulletin.html.

Does Southwest Missouri Face a Future Water Shortage?


Southwest Missouri faces a water crisis. If nothing is done, demand will exceed current supply by 2030. However, sufficient additional water to meet demand through 2060 appears to be available, and could be accessed at a relatively low cost. Whether doing so would impact the regions ecosystem is not known.


In the previous post, I reported that current stresses on water supply along the Missouri River depend primarily on human decisions about how to manage competing demands for the river’s water. The future effects of climate change are not yet known.

What about regions of the state that don’t depend on the Missouri River for their water supply? Are demands projected to exceed supply?

To answer that question, we must start by distinguishing between water resources and water supply. Water resources consist of the total water available in a region. Water supply is the amount of water that the infrastructure is capable of delivering.

Water resources consist of surface water and groundwater. Some regions of the state depend primarily on surface water. In fact, surface water supplies 8 of Missouri’s 10 largest cities, and 62% of the state’s total water consumption (44% from the Missouri River alone). Groundwater supplies about 38% of Missouri’s water consumption. Some regions, however, rely more heavily on groundwater, especially in the southern part of the state.

Figure 1. Southwest Missouri Counties Expected to Experience a Future Water Shortage. Source: Adapted from a map at Wikimedia Commons.

No region of the state is currently experiencing a sustained shortfall in water supply compared to demand. Perhaps the region most likely to experience one in the future is a 16 county area in Southwest Missouri. Figure 1 shows a map of the 16 counties.

The region has historically depended primarily on groundwater, as it is underlain by the Ozark Aquifer. Aquifer levels fluctuate depending on how much precipitation occurs to recharge them. In addition, over-pumping can deplete the water supply in a local region of the aquifer faster that water can flow in to replace it, causing a cone of depression. It can leave neighboring wells high and dry, but does not affect the whole aquifer. Severe over-pumping from multiple sources can deplete the entire aquifer, which is occurring in California.

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Figure 2. Missouri Population Density. Source: Tri-State Water Coalition.

The region’s constraints on water supply have occurred because of growth. Figure 2 is a map of population density in Missouri. It shows that Southwest Missouri is one of the more densely populated regions.

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Figure 3. Source: Tri-State Water Resource Coalition.

Figure 3 shows that from 1990-2000 the region was the fastest growing in the state. Between 2000 and 2010, the trend continued, with Christian County growing an astounding 43% and Taney County growing by 30%.

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Figure 4. Source: Tri-State Water Resource Coalition

The result has been over-pumping, and Figure 4 shows the results. In Southwest Missouri, most areas have experienced some decrease in the groundwater level. A few regions in Green County (the City of Springfield), Jasper County (the City of Joplin), and Stone and Taney Counties (the Branson area) have experienced cones of depression, dropping the water table more than 300 feet. The worst affected area is the large red area on the left side of the map. It is in Oklahoma, centered on Miami, OK.

Using a mid-level growth forecast, studies have calculated that current water resources will be overrun by demand by 2030. Even reducing demand through conservation would only meet needs through 2040.

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Figure 5. Projected Water Demand and Supply by 2060 in a Drought Year. Source: Tri-State Water Resource Coalition.

The region has significant surface water resources, however, and could supplement its water supply. Three significant reservoirs could supply water to the region: Stockton Lake, Table Rock Lake, and Lake Taneycomo. The first two are operated by the U.S. Army Corps of Engineers, and the latter is owned and operated by Empire District Electric Company. These organizations would have to approve the reallocation of water, but the water is there. Figure 5 shows projected available supply and demand if surface water resources were tapped. It would require the construction of pipelines and pumping stations, but the dams and reservoirs already exist.

Climate change is not projected to cause a decrease in precipitation in the region. The worst drought on record occurred in the 1950s, and if anything, the trend in precipitation has increased slightly since 1895. The temperature is projected to increase significantly, however. If increased temperature were to lead to less water reaching the aquifer to recharge it, then it could have implications for the regions water supply. But so far, those projections have not yet been calculated.

Unfortunately, none of the reports I contacted discuss the environmental impacts that the increasing demand for water will place on the ecosystem in the region. In fact, so far as I could tell, possible effects were not even considered. Will dropping water tables cause springs, creeks, and rivers to go dry? Will reallocation of the water from the regions reservoirs affect the health of the White and Osage Rivers? Will subsidence occur? These effects have occurred elsewhere, why Missouri would expect to be immune from them? But I just don’t know.

Thus, it appears that Southwest Missouri does face a water crisis. If nothing is done, demand will exceed current supply by 2030. However, sufficient additional water to meet demand through 2060 appears to be available, and could be accessed at a relatively low cost. Whether doing so would impact the regions ecosystem is not known.

Sources:

Missouri Department of Natural Resources. Springfield Plateau Groundwater Province. Downloaded 5/23/2017 from https://dnr.mo.gov/geology/wrc/groundwater/education/provinces/springfieldplatprovince.htm?/env/wrc/groundwater/education/provinces/springfieldplatprovince.htm.

State of Missouri and U.S. Army Corps of Engineers. 2012. Southwest Missouri Water Resource Study – Phase I. Downloaded 5/23/2017 from http://www.swl.usace.army.mil/Portals/50/docs/planningandenvironmental/Phase%20I%20-%20Southwest%20Missouri%20Water%20Study%20Final%20Report%20.pdf.

State of Missouri and U.S. Army Corps of Engineers. 2014. Southwest Missouri Water Resource Study – Phase II. Downloaded 5/23/2017 from http://tristatewater.org/wp-content/uploads/2014/11/Phase-II-FINAL-Southwest-Missouri-Supply-Availability-Report-Final_March_2014-from-Mike-Beezhold-9-16-14.pdf.

Tri-State Water Resource Coalition. 2015. Securing Water for Southwest Missouri. Downloaded 5/30/2017 from https://waterways.org/wordpress1/wp-content/uploads/2015/05/Securing-Water-for-Southwest-Missouris-Future.pdf.

Will Climate Change Affect Water Supply on the Missouri River?


How climate change will affect water supply from the Missouri River is not yet known. Current problems with Missouri River water supply principally affect the barge transportation industry, and the agricultural and industrial clients that use it to transport their goods and supplies.


The Missouri River is important for Missouri. More than half of Missouri residents get their drinking water from the Missouri River or the alluvial aquifer it directly feeds. Not only that, the river’s water is used for agricultural irrigation, for industry, to support barge traffic along the Missouri and Mississippi Rivers, for recreation, and to support the ecosystems that depend on the river for their survival.

Figure 1. Dams and Other Locations Along the Missouri River. Source: Google Earth.

In the previous post, I reported that the snowpack in the western United States has declined by 23%, and it is forecast to decline more by 2038. The eastern border of the study area forms the western boundary of the Missouri River Basin. Will the changing western snowpack impact the Missouri River’s ability to supply Missouri’s needs?

The answer is complicated. Precipitation in the Upper Missouri River Basin has historically fallen mostly as snow, building a winter snowpack that slowly melts during the spring. The snowmelt is gathered into reservoirs created by 6 large dams along the Missouri River, plus more than 40 smaller ones on tributaries. The 6 large dams begin at the Gavin’s Point Dam on the Nebraska-South Dakota border, and extend upriver to the Ft. Peck Dam in Montana. (See Figure 1.) The result is that water flow below the reservoirs is largely controlled by man, not nature.

Figure 2. Data source: Wikipedia.

The annual water yield from the Missouri River is small compared to the size of its basin. The data is given in Figure 2, where the red columns represent the length of the rivers, and the blue line represents their average discharge. No other river in the USA serves such a large basin with so little water. In drought years it is already too small to fully meet all of the demands that are put on it, resulting in conflict over how to manage the river, and over which values to give priority. The conflict has primarily been between up-river interests, which would like to see water allocated to support irrigation, drinking water, and mitigation in their states during periods of drought, and down-river interests, which would like to see water released to support commercial navigation on the river.

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Figure 3. Source: Hansen Professional Services, Inc. 2011.

In 2004, the Army Corps of Engineers changed the rules by which the river is operated to reduce water releases during drought. During drought years, this better supports up-stream interests, but results in a shorter season during which the river can support barge traffic. The result has been a decrease in annual tonnage moved on the river (Figure 3).

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Figure 4. Well Drilling in Western North Dakota. Source: Vanosdall 2013.

In addition, development in the Upper Missouri Basin has increased water demand in that region. A prime example would be the development of the oil and gas reserves in North Dakota. Well drilling uses large quantities of water. (See Figure 4). Given that the water yield from the Missouri River is already too small to fully support all of the demands placed on it, any increase in demand is bound to constrain supply even further.

The constraints discussed above, however, are all man-made constraints. How will climate change and the declining western snowpack affect all of this?

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Source: National Centers for Environmental Information.

The snowpack decline has occurred because of increasing temperature, not decreasing precipitation. Figures 5 repeats a chart I published in January 2016, showing that precipitation has increased in the region over time.

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Figure 6. Source: Melillo 2014.

Figure 6 shows that the 2011 National Climate Assessment projects that the annual flow on the Missouri River will actually increase by about 15% by 2070. However, more precipitation will fall as rain instead of snow, and the snow that does fall will melt sooner. This means that more water will enter the reservoirs during winter and early spring, and less during late spring and summer. In addition, increased temperature will increase evaporation from the river and reservoirs, and it will increase water consumption by crops, leading to earlier and increased demand for water. There is a potential mismatch between when the water is available and when it is needed.

The question will be whether it will be possible to manage the reservoirs successfully under the new conditions. When looking at the water situation in California (here), we discovered that water authorities expected climate change to create reservoir management problems that would result in an increased water deficit during the summer and autumn. It is possible that the reservoirs along the Missouri will encounter similar problems, but it is not certain.

One potential difference is that California has multiple, relatively short rivers, leading to only one large reservoir per river, and perhaps one or two small feeder reservoirs. The Missouri River, however, is a single long river. It has 6 large reservoirs chained along it, plus at least 40 feeder reservoirs on tributaries. This may give managers flexibility in managing the river that is not possible in California.

Five separate water resource studies have been undertaken to determine how climate change will impact the ability of the Missouri River to meet the demands placed on it. Unfortunately, they have not all been completed, and I can find no comprehensive analysis.

For the time being, problems with water supply on the Missouri River involve human decisions about how to manage the river. To date, in the State of Missouri they have primarily impacted the barge industry, plus the farmers and industries that depend on the barge industry to transport their goods and supplies.

Sources:

Drew, John, and Karen Rouse. 2006. “Missouri Water in High Demand.” Missouri Resources, Winter, 2006. Downloaded 5/31/2017 from https://dnr.mo.gov/geology/wrc/docs/Water-InHighDemand.pdf?/env/wrc/docs/Water-InHighDemand.pdf.

Bureau of Reclamation. 2016. Basin Report: Missouri River. Downloaded 5/25/2017 from https://www.usbr.gov/climate/secure/docs/2016secure/factsheet/MissouriRiverBasinFactSheet.pdf.

Bureau of Reclamation. 2016. SECURE Water Act Section 9503(c) – Reclamation Climate Change and Water. Prepared for United States Congress. Denver, CO: Bureau of Reclamation, Policy and Administration. Downloaded 5/25/2017 from https://www.usbr.gov/climate/secure.

Hanson Professional Services, Inc. 2011. Missouri River Historic Timeline and Navigation Service Cycle. Missouri River Freight Corridor Assessment and Development Plan. Downloaded 5/31/2017 from https://library.modot.mo.gov/rdt/reports/tryy1018.

Melillo, Jerry M., Terese (T.C.) Richmond, and Gary W. Yohe, Eds., 2014: Climate Change Impacts in the United States: The Third National Climate Assessment. U.S. Global Change Research Program, 841 pp. doi:10.7930/J0Z31WJ2. Available online at http://nca2014.globalchange.gov.

Vanosdall, Tiffany. 2013. Missouri River Water Supply. US Army Corps of Engineers. Downloaded 6/1/2017 from https://denr.sd.gov/coewatersupply22Apr2013.pdf.

Wikipedia. List of U.S. Rivers by Discharge. Data retrieved online 5/31/2017 at https://en.wikipedia.org/wiki/List_of_U.S._rivers_by_discharge.

Declining Snowpack in the American West


The snowpack over the western United States has declined about 23% since 1981. It is projected to decline more in the future.


I have written a number of posts about the looming water deficit in California due to a projected decline in the snowpack on the Sierra Nevada mountains. Is something similar projected to occur throughout the entire western United States?

Figure 1. Change in Snow Water Equivalent at SNOTEL Stations, 1955-2016. Source: Mote and Sharp 2016, in Environmental Protection Agency, 2016.

Yes. Studies find that the water content of the snowpack throughout the West has already declined 23%, and it is expected to decline more, perhaps up to 30% by 2038.

This decline is not occurring via a decrease in precipitation. Indeed, to date precipitation across the West has actually increased slightly. The decline is occurring due to increased temperature. Some precipitation that used to fall as snow now falls as rain, and the snow that does fall melts more quickly.

Mote and Sharp studied the snow water equivalent* of the snowpack in April from 1955-2016 at SNOWTEL measuring stations operated by the U.S. Natural Resource Conservation Service. Figure 1 shows a map of the stations, with blue dots representing stations where the snowpack increased and orange dots representing stations where the snowpack declined. The size of the dots represent the magnitude of change.

It is easy to see that the vast majority showed declines in the snowpack, in many cases by as much as 80%. Overall, Mote and Sharp computed that there had been an average 23% decline in the western snowpack since 1955.

 

Figure 2. Observed and Modeled Change in Snowpack. Source: Fyfe, et al, 2017.

Fyfe and his colleagues conducted climate modeling to try to determine whether the decline in the snowpack was due to natural causes or human causes. Figure 2 shows the results in a rather complicated graph. Let’s unpack it. The computer models ran from 1950 to 2010. The dashed black line shows the observed trend in the snow water content. The solid blue line shows the projected snow water content if only natural climate causes are included in the model. It doesn’t fit the observed trend very well. The solid black line shows the projected snow water content if both natural and human climate causes are included in the model. It fits the observed data quite closely. (The pink and green lines show data from analyses using other sets of data and need not concern us here. The gray band and blue dotted lines show statistical confidence levels for the computer simulations, and also need not concern us here.)

The simulation that included both natural and human causes agreed with the observed data, but the one that included only natural causes did not. The authors concluded that natural causes could not explain the loss of snowpack in the West. A combination of human and natural causes could explain it.

Figure 3. Projected Short-Term Change in Snowpack. Source: Fyfe, et al, 2017.

Fyfe and his colleagues also conducted a suite of climate models to project snowpack loss into the future. The results are shown in Figure 3. In this graph, the y-axis represents the actual snow water content of the snowpack, not the change. The blue line represents the computer model that projected the least snowpack loss in 2030, and the red line represents the computer model that projected the most loss. It is common practice among climate modelers to run a suite of projections, and when this is done, the average of them is often also presented, and it is often taken as likely to be the most accurate. In Figure 3, the average of the projections is represented by the black line.

It is easy to see that the trend in all of the lines is down. There is considerable variation from point-to-point in the red and blue lines, indicating that the projections expect there to be considerable variability in the snowpack from year-to-year. The black line is pretty smooth, however, as might be expected from an average of several analyses, and it has a consistent downward trend. The losses in snowpack in some of the projections ran as high as 60%, though average loss across the suite of projections was about 30%.

A 30% decline in the snowpack does not sound so dire; after all the projections are for a 60% loss of snowpack in California (see here). However, that projection was for the end of the century. This projection is for 2038; that’s only 20 years from now.

Some may wonder about how little snow water equivalent is shown on the y-axis of Figure 3. In the 1990s, the snowpack maxed-out each year at only 6+ cm. of snow water equivalent. In thinking about this number, remember two things: first, a centimeter of water represents somewhere between 3 and 20 centimeters of snow, with an average value being somewhere around 10 cm. Thus, 6 cm. of snow water equivalent would roughly equal 60 cm. of snow, or 23.6 inches. Thus, the average depth of the snowpack was about 2 feet. Second, remember that the measurements were averaged across hundreds of locations; some were high and received a great deal of snow, but some were relatively low (low altitude means more rain, less snow), or were located in areas that don’t receive much precipitation of any kind.

Much of Missouri depends on the Missouri River as a water supply, including both Kansas City and St. Louis. The Missouri River gets much of its water from the western snowpack. A declining snowpack may, or may not, have implications for our water supply, depending on whether the reservoirs along the Missouri River can accommodate the shift toward earlier snowmelt and increased rain. I will look at this issue in the next post.

*   Snow water equivalent: Different types of snow hold different amounts of water. Thus, scientists don’t just measure how deep the snow is. Rather, at a given location they take a representative sample of the snowpack and melt it, thereby determining how much water it holds. This is the snowpack’s snow water equivalent at that given location. April is generally when the snowpack is at its maximum.

Sources:

Environmental Protection Agency. 2016. Climate Change Indicators in the United States: Snowpack. Retrieved online 5/22/2017 at https://www.epa.gov/sites/production/files/2016-08/documents/print_snowpack-2016.pdf.

Fyfe, John, Chris Kerksen, Lawrence Mudryk, Gregory Flato, Benjamin Santer, Neil Swart, Noah Molotch, Xuebin Zhang, Hui Wan, Vivek Arora, John Scinocca, and Yanjun Jiao. 2017. “Large Near-Term Projected Snowpack Loss Over the Western United States.” Nature Communications, DOI: 10.1038/ncomms14996. Retrieved online 5/14/2017 at https://www.nature.com/articles/ncomms14996.

Missouri Burden of Disease

In the last two posts I looked at a report that attempted to quantify the burden of disease attributable to environmental factors. It was produced by the World Health Organization (WHO), and its analysis concerned the whole earth.

The Missouri Department of Health and Senior Services produced a report on the burden of chronic diseases in Missouri in 2013. The report makes interesting reading, though it is not equivalent to the WHO report.

Figure 1. Source: Yun et al, 2013.

Of the top 8 causes of death in Missouri during 2010, 7 were chronic diseases. (Figure 1) Together, they caused 68.2% of all deaths in Missouri. Heart disease and cancer caused by far the most, between them accounting for almost half of all deaths.

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Figure 2. Source: Yun et al, 2013.

If one defines premature death as death occurring before age 65, then 14,827 Missourian’s died prematurely in 2010. As shown in Figure 2, chronic diseases caused 58.4% of the deaths, cancer and heart disease again leading the way, causing 46% of all premature deaths.

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Figure 3. Source: Yun et al, 2013.

Almost 3 in 4 Missourians (74.4%) were affected by at least one of 13 major chronic conditions, as shown in Figure 3 (individuals may be affected by more than one condition, thus the percentages do not sum to 100%). More than 1/3 of Missourians were living with cholesterol and hypertension, conditions which are not fatal in themselves, but which contribute to many other diseases that are. The prevalence of each of these conditions was higher in Missouri than nationally, except for vision impairment, which occurred in Missouri about at the same rate that it does nationally.

The mortality rates for heart disease, cancer, stroke, and diabetes all declined significantly in Missouri between 2000 and 2009. Prevalence rates did not, however, and for some chronic diseases prevalence rates actually increased. Thus, it seems that Missouri has made progress managing chronic diseases, but not preventing them.

The Missouri report did not address environmental factors that cause disease. To the extent that the report did consider risk factors, it focused on demographic characteristics, personal habits, and the social environment, such as the availability of health care, the availability of healthy food, and second-hand smoke. While some of these overlap with the WHO report to a limited degree, the Missouri report did not consider ecological factors such as air pollution and exposure to toxic chemicals. Despite the fact that ecological factors contribute strongly and obviously to several of the chronic conditions from which Missourians suffer, such as cancer and chronic lower respiratory disease, I could find no report addressing the issue in Missouri. If any of you know of one, please let me know.

Sources:

Yun S, Kayani N, Homan S, Li J, Pashi A, McBride D, Wilson J. 2013. The Burden of Chronic Diseases in Missouri: Progress and Challenges. Jefferson City, MO: Missouri Department of Health and Senior Services. Downloaded 5/2/2017 from http://health.mo.gov/atoz/pdf/burdenofchronicdiseasesinmissouri.pdf.

Disease Burden Attributable to Environmental Factors


Environmental factors play a surprisingly large role in the disease burden with which humankind must cope.


Figure 1. Global Deaths and Disability-Adjusted Life Years Attributable to the Environment. Source: Prüss-Ustün et al, 2016.

In 2012, 12.6 million deaths worldwide (22.7% of all deaths) were attributable to environmental causes, as were 596 million disability-adjusted life years (DALYs) (21.8% of all DALYs)*. (Figure 1) So says a report issued in 2016 by the World Health Organization. I reviewed some of the report’s findings in the previous post. In this post, I turn to its findings regarding specific disease conditions.

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Figure 2. Source: Prüss-Ustün et al, 2016.

The report authors found that 13 types of diseases or disease groups had the highest preventable disease burden from environmental risks. Figure 2 shows the raw number of DALYs attributable to environmental factors by disease group. Cardio-vascular diseases account for the largest disease burden worldwide, causing 119 million DALYs in 2012, some 60% more than unintentional injuries, the second largest category. Road injuries were counted separately from unintentional injuries, however. I suspect that road injuries are mostly unintentional (though road conditions and driving habits may sometimes argue otherwise). If you combine the two categories, then accidents account for 105 million DALY’s just slightly less than cardio-vascular diseases.

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Figure 3 shows the same data, but in a different way. For each of the disease groups, it shows the percentage of total cases that can be attributed to the environment. Thus, 57% of all diarrheal diseases can be attributed to environmental causes, the highest fraction. Fifty percent of all unintentional injuries have environmental causes (I think this means that they can be attributed to unsafe conditions that could be remedied, like working in the diamond mines of the Ivory Coast).

Many of the conditions shown in Figures 1 and 2 are disease groups. Looking at specific individual conditions, the report found that fully 76% of fires and burnings could be attributed to environmental conditions, as could 73% of drownings and 57% of diarrheal diseases. The data start to sound almost like public safety or public health issues, as opposed to what we typically think of as “environmental” here in America. And perhaps, in many parts of the world, that is exactly right.

Figure 4. Recommended Actions by Disease Group. Source: Prüss-Ustün et al, 2016.

The authors make recommendations regarding which environmental interventions they thought would be most likely to significantly reduce the burden of environmentally caused disease for each of the 13 disease groups. The recommendations are shown in Figure 4. For those conditions most relevant in the United States (cardio-vascular disease and cancer) it is interesting to see that, along with second-hand smoke, household and ambient air pollution were thought to be important. I’ve discussed the progress Missouri has made in improving its ambient air quality several times, most recently here. We often ignore indoor air quality when we discuss air pollution, however. I don’t know how you would measure it across millions of buildings, but it is a very important environmental issue. If anybody knows about studies of indoor air pollution across Missouri or across the USA, please let me know.

I’ll try to bring all of this home to Missouri a little bit in the next post.

*Disability-Adjusted Life Year (DALY). Disability-adjusted life year is a measure used to estimate the number of years lost to early death, combined with the number of years lost to disability. To determine the number of years lost to death for an individual, subtract the age of death from the normal life expectancy. The result represents the number of years lost to death. For disabilities, subtract the age at which the disability occurred from normal life expectancy, then multiply the result by a “disability factor,” which represents the severity of the disability. The result represents the years lost to disability. Add the years lost to death and the years lost to disability, and you have the disability-adjusted life years (DALYs) for that individual. Do this calculation for every individual in the group, and sum the results across the group, and you have the DALYs for the group.

Sources:

Prüss-Ustün, A., J. Wolf, C. Corvalán, R. Box, and M. Neira. 2016. Preventing Disease Through Health Environments: A Global Assessment of the Burden of Disease from Environmental Risks. WHO Press: Geneva. Downloaded 5/3/2017 online from http://www.who.int/quantifying_ehimpacts/publications/preventing-disease/en.

Death and Disease from the Environment


In 2012…12.6 million deaths globally, representing 23%…of all deaths, were attributable to the environment. When accounting for both death and disability, the fraction of the global burden of disease due to the environment is 22%… In children under five years, up to 26%…of all deaths could be prevented, if environmental risks were removed.


So begins the Executive Summary of Preventing Disease Through Health Environments: A Global Assessment of the Burden of Disease from Environmental Risks, a report issued by the World Health Organization (WHO). Those of us who think of the environment as the necessary support of all life on Earth may not find their claim surprising, but it is pretty dramatic: more than 1 death in every 5. Let’s look at what it means. This post will discuss some preliminaries and look at broad conceptual findings. The next post will look at specific disease burdens.

The authors looked at 133 types of diseases or injuries and found that 101 of them had significant links with the environment. They were able to quantify, at least partially, the environmental contribution for 92 of them. The 92 conditions run the gamut, including:

  • infectious diseases, such as malaria and diarrhreal diseases;
  • neonatal and nutritional conditions, like malnutrition and birth defects;
  • non-communicable diseases, like cancer or neurological disorders;
  • unintentional injuries, such as road traffic accidents or unintentional poisonings;
  • intentional injuries, such as self-harm or interpersonal violence; and
  • risk factors that contribute to non-communicable diseases of other types, but which are related to the environment, such as obesity and physical inactivity.

Figure 1. Source: Prüss-Ustün et al, 2016.

Some of these may seem controversial to an American public, seeming like personal choices. The authors contend, however, that each of them contributes to death or disease, and each of them has an identifiable link to environmental factors that are modifiable by people.

As one might expect, the fraction of deaths attributable to the environment is higher in poorer countries, lower in wealthy countries (Figure 1). There are several reasons for this. One is that wealthier nations are able to afford better environmental protections. Another is that wealthier nations have been able to transition to safer methods of doing almost everything (from transportation, to industrial processes, to cooking and home heating).

Figure 2. Percent Attributable to Environmental Causes, by Disease Type and Region. Source: Prüss-Ustün et al, 2016.

The type of disease impacted by the environment also varies by region (Figure 2). In Sub-Saharan Africa environmental factors cause a high number of per capita deaths from infectious, parasitic, neonatal, and nutritional diseases. Examples might include malaria, diarrheal diseases, and malnutrition. But in Europe, Southeast Asia, the Western Pacific, and High-Income OECD Nations, environmental factors cause high numbers of per capita deaths from non-communicable diseases. Examples might include cancer and heart disease.

Some background information may help in understanding the report’s findings. It is rare for the environment to sicken or kill somebody outright. Typically, the environment leads to some other condition that is the direct cause of illness or death. For instance, desertification may lead to famine, but starvation may be listed as the direct cause of death, not desertification. A contaminated water supply may lead to cholera, but cholera may be listed as the direct cause of death, not contaminated water. Asbestos may led to mesothelioma, but mesothelioma may be listed as the direct cause of death, not asbestos.

Figure 3. Conditions Environmentally Caused: Included and Excluded. Source: Prüss-Ustün et al, 2016.

The WHO report defines environmental risks broadly. Figure 3 shows what is included and what is excluded. Diseases that involve person-to-person interaction, or that result from personal habits and choices are excluded. Also excluded are disease vectors that exist in the environment, but which can’t readily be modified (for instance, pollen). Included are factors that most people would regard as environmentally modifiable (e.g. exposure to chemicals or air pollution). Thus, mesothelioma caused by asbestos exposure would be included, but getting the flu from somebody at work would not be.

Nobody keeps records of environmental exposure leading to death, especially in the undeveloped world. Thus, it has to be estimated. The report used several types of estimates which require the use of assumptions and/or expert opinion. Thus, be sure to keep in mind that the report represents an estimate. It is almost certain to contain errors, though it may be the best estimate available.

The next post will look at specific disease conditions, and what fraction of the disease burden can be attributed to environmental factors.

Sources:

Prüss-Ustün, A., J. Wolf, C. Corvalán, R. Box, and M. Neira. 2016. Preventing Disease Through Health Environments: A Global Assessment of the Burden of Disease from Environmental Risks. WHO Press: Geneva. Downloaded 5/3/2017 online from http://www.who.int/quantifying_ehimpacts/publications/preventing-disease/en.